The production and storage of images in synchronous digital video provide potential advantages over other ways of recording images, such as conventional analog video images stored on magnetic tape for display on television sets (e.g., VCR tape). For example, digital video images permit a user to scan and access specific time frames within the video with a minimal amount of access time. In conjunction with computing systems having suitable processing and storage facilities, the use of synchronous digital video becomes a practical medium for a variety of applications.
One specific application of synchronous digital video involves measuring and/or monitoring movement of objects within video images. For example, when a patient undergoes an electroencephalogram (“EEG”), a testing facility is generally interested in acquiring a sufficient amount of data to detect and quantify the amount of movement by the patient (in terms of how much and for how long). Often, each monitoring period lasts over several hours and a single patient may undergo multiple EEG tests within a period of a few weeks.
Some testing facilities utilize digital video to record the patient over the entire monitoring period, and then use the scanning features of the digital video to pass through any extended periods of patient inactivity. Generally, the testing facility must balance the quality/quantity of the video data with the financial burden of collecting data in terms of the amount of memory required to capture and store video images. For example, a sleeping patient being monitored throughout an entire night (approximately a period of eight hours) may only produce minutes of detectable movement throughout the entire eight hours. Requiring the testing facility to record and maintain the entire eight-hour synchronous video becomes resource depleting and an inefficient use of typically expensive computing resources, especially if this type of testing is repeated often and conducted on a large patient group.
To alleviate the resource consuming deficiency associated with synchronous digital video images, various digital video formatting methods are utilized to reduce the amount of data required to store and recreate video images. One example of a compression-type video formatting method is the Motion Picture Engineering Group (“MPEG”) video format. In accordance with the MPEG format, a continuous video image is broken down into a number of successive still video frames over a given time period. Additionally, the MPEG formatting method is configured such that the data packet size required to generate each of these successive frames is approximately equal. One skilled in the relevant art will appreciate that most compression techniques, such as the MPEG format, are lossy in that the restored image is an imperfect copy of the original. Additionally, most compression techniques introduce some type of artifacts whose character and severity may be controlled by modifying the type and degree of compression.
One approach utilized by lossy compression techniques, such as the MPEG formatting method, involves reducing the amount of data necessary to create a successive frame by varying the amount of detail information utilized to create each video frame. One skilled in the relevant art will appreciate that the amount of detail information utilized to generate each frame is directly related to the amount of change the current frame will display as compared to the preceding frame. For example, if a current frame of data is different from the preceding frame, it is assumed that the current frame will require a greater amount of data to be generated. Accordingly, under this approach, the amount of data used to generate detail in the current frame is reduced to maintain the constant sized data packets. However, because a change in subsequent frames implies movement within the video image, the reduced frame resolution by the loss of detail information is typically unnoticeable (or at least acceptable) to the human eye.
Another approach utilized by lossy compression techniques involves reducing the amount of data necessary to create and store by capturing and storing only the difference between the successive frames if the two images within the frames are considered to be substantially similar. For example, if only a small percentage of a frame of digital data is changed from the previous frame, only the pixel data that has changed will be transmitted. Thus, this approach mitigates the amount of the data transferred by eliminating the transmission of non-changing pixel data.
Although conventional lossy video image compression formats, such as the MPEG video format, attempt to reduce the amount of data required to store and recreate synchronous video images, these conventional formats are not well suited for specific application to the detection and quantification of movement over extended periods of time while maintaining smaller sized data files. With reference to the use of video data to conduct an EEG procedure on a patient, the necessary quality of images required to monitor movement under the MPEG formatting method creates approximately one gigabyte of data per hour. Considering that a single patient generates approximately eight hours of data per test period, use of the MPEG format would quickly consume large quantities of testing facility processing and memory storage resources. Moreover, the MPEG format does not provide any quantification or measurement of the amount of movement with the video image.
Accordingly, there is a need for a method and system that provides variable compression data rates as a function of the amount of movement between successive frames of a video image. Additionally, there is a need for a method and system for detecting and quantifying movement within a synchronous video image.